PURPOSE Measurement of vertebral axial rotation (VAR) is relevant for the assessment of scoliosis. Stokes method allows estimating VAR in frontal X-rays from the relative position of the pedicles and the vertebral body. This method requires identifying these landmarks for each vertebral level, which is time-consuming. In this work, a quasi-automated method for pedicle detection and VAR estimation was proposed. METHOD A total of 149 healthy and adolescent idiopathic scoliotic (AIS) subjects were included in this retrospective study. Their frontal X-rays were collected from multiple sites and manually annotated to identify the spinal midline and pedicle positions. Then, an automated pedicle detector was developed based on image analysis, machine learning and fast manual identification of a few landmarks. VARs were calculated using the Stokes method in a validation dataset of 11 healthy (age 6-33 years) and 46 AIS subjects (age 6-16 years, Cobb 10°-46°), both from detected pedicles and those manually annotated to compare them. Sensitivity of pedicle location to the manual inputs was quantified on 20 scoliotic subjects, using 10 perturbed versions of the manual inputs. RESULTS Pedicles centers were localized with a precision of 84% and mean difference of 1.2 ± 1.2 mm, when comparing with manual identification. Comparison of VAR values between automated and manual pedicle localization yielded a signed difference of - 0.2 ± 3.4°. The uncertainty on pedicle location was smaller than 2 mm along each image axis. CONCLUSION The proposed method allowed calculating VAR values in frontal radiographs with minimal user intervention and robust quasi-automated pedicle localization. These slides can be retrieved under Electronic Supplementary Material.

中文翻译：

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使用准自动椎弓根检测方法根据额线X射线估算椎骨旋转度。

目的椎骨轴向旋转度（VAR）的测量与脊柱侧弯的评估有关。斯托克斯方法允许从椎弓根和椎体的相对位置估计额X射线中的VAR。该方法需要为每个椎骨水平识别这些界标，这很费时。在这项工作中，提出了一种用于椎弓根检测和VAR估计的准自动化方法。方法这项回顾性研究共纳入149名健康和青少年特发性脊柱侧凸（AIS）受试者。他们的额线X射线是从多个部位收集的，并进行了人工注释，以识别脊柱中线和椎弓根的位置。然后，基于图像分析，机器学习和一些地标的快速手动识别，开发了一种自动椎弓根检测器。使用Stokes方法在11名健康者（6-33岁）和46名AIS受试者（6-16岁，Cobb 10°-46°）的验证数据集中计算VAR，均来自检测到的椎弓根和手动标注的椎弓根他们。使用10种扰动的手动输入版本，对20名脊柱侧弯受试者进行了椎弓根位置对手动输入的敏感性的量化。结果与人工识别相比，椎弓根中心定位精度为84％，平均差异为1.2±1.2 mm。自动和手动椎弓根定位之间的VAR值比较产生了-0.2±3.4°的显着差异。沿着每个图像轴的椎弓根位置的不确定度均小于2 mm。结论所提出的方法允许在最小的用户干预和鲁棒的准自动椎弓根定位的情况下在额骨X线片中计算VAR值。这些幻灯片可以在电子补充材料下找到。